Data Envelopment Analyses
Zeynab Latifi; Neda Pouyan
Abstract
Purpose: Data Envelopment Analysis, one of the keys subfields in mathematical planning, has found a prominent role in evaluating the efficiency of decision making units in various fields. Methodology: In this research, after analysis and initial processing, based on studies, a parametric and efficient ...
Read More
Purpose: Data Envelopment Analysis, one of the keys subfields in mathematical planning, has found a prominent role in evaluating the efficiency of decision making units in various fields. Methodology: In this research, after analysis and initial processing, based on studies, a parametric and efficient method for ranking intuitionistic fuzzy numbers is selected and proposed. The correctness of the performance of the selected method is obvious due to its formulation in linear structures. The developed model of data envelopment analysis, its mathematical formulation by CCR and IO-BCC methods are expressed in terms of governing the model structure and its implementation approach. A case study is presented to determine the factors affecting safety performance using the model. Based on previous theoretical studies and opinions of experts in the field of safety, the most important influencing factors (work pressure and perception of the supervisors' safety as inputs) and (the rate of physical and mental injuries and unsafe accidents as outputs) were selected. In addition to ranking the units, sensitivity analysis was performed in CCR and IO-BCC methods to rank the specified indicators in the inputs and outputs, and the results have been compared.Findings: The results of the data envelopment analysis model with intuitionistic fuzzy data showed that with increasing k, the number of efficient units increases. On the other hand, in CCR and IO-BCC methods, the lowest and highest efficiencies belong to the pessimistic view (k = 0) and the balanced view (k = 0.5), respectively. Sensitivity analysis also showed that, in CCR and IO-BCC methods, the work pressure is the most safety factor affecting the efficiency results.Originality/Value: Using a Data Envelopment Analysis model with intuitionistic fuzzy data to evaluate the performance of construction sites from a safety perspective can provide significantly better results. Because in the real world, there is uncertainty, and intuitionistic fuzzy data, due to the concept of belonging, non-belonging, and suspicion in the view of decision-makers simultaneously and in data reporting, is of particular importance.
Fuzzy Optimization
Madineh Farnam; Majid Darehmiraki
Abstract
Purpose: In working with Interval-valued intuitionistic fuzzy sets according to considering the membership and non-membership function simultaneously, as well as the interval of the data type, we face to a lot of flexibility to allocate data by the decision maker. Comparison ...
Read More
Purpose: In working with Interval-valued intuitionistic fuzzy sets according to considering the membership and non-membership function simultaneously, as well as the interval of the data type, we face to a lot of flexibility to allocate data by the decision maker. Comparison between them, as one of the first concepts in the decision-making process, does not seem so simple. For this purpose, in this paper we present an integrated and efficient method and a new way to prioritize interval-valued intuitionistic fuzzy numbers. Then we apply this method to assess the qualitative qualification of contractors.Methodology: Use interval valued intuitionistic fuzzy sets along with multi criteria decision making.Findings: New ranking method of interval valued intuitionistic fuzzy sets is apllied in evaluating operational units. In addition, by giving a practical example while describing the process performance, the output of the work is observed.Originality/Value: A new method is proposed to determine the preference between interval valued intuitionistic fuzzy sets. In addition, an efficiency process is introduced to assess the qualitative qualification of contractors.